스마트폰에서의 다속성 기반 다중 네트워크 운용 최적화 기법 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 2. 최성현.Todays smartphones integrate multiple radio access technologies (multi-RAT), e.g., 3G, 4G, WiFi, and Bluetooth, etc. Moreover, state-of-the-art smartphones can activate multiple RAT interfaces simultaneously for the parallel transmission. Therefore, it is becoming more important to select the best RAT set among the available RATs, and determine how much data to transfer via each selected RAT network. We propose Energy, Service charge, and Performance Aware (ESPA), an adaptive multi-RAT operation policies for smartphone with supporting system design and multi-attribute cost function for smartphones Internet services including multimedia file transfer and video streaming services. ESPAs cost function incorporates battery energy, data usage quota, and service specific performance, simultaneously. These attributes are motivated by the growing sensitivity of todays smartphone users to these attributes. Each time the individual attributes are calculated and updated, ESPA selects the optimal RAT set that minimizes the overall cost. It can activate only the best one RAT interface or exploit multiple RATs simultaneously. The primary benefit of the ESPA is that it enables the smartphone to always operate in the best mode without the need for users manual controlthe energy saving mode if the remaining battery energy is becoming nearly depletedthe cost-saving mode if the remaining data quota is almost running outor, the performance-oriented mode if remaining data quota and battery energy are both sufficient. From Chapter 2 to Chapter 4, we cope with file transfer, video streaming, and standby mode for our proposed algorithms. The proposed algorithms are based on the service specific cost or utility models, which also take into account practical issues related to user satisfaction metrics. First, for file transfer mode, we apply the transfer completion time as the performance metric, and the energy consumption and service charge for downloading a specific size of file are simultaneously considered. Furthermore, we especially take into account a problem that the computational complexity exponentially increases as the number of available RATs increases. We propose a heuristic linear search algorithm to find the optimal RAT set without significant performance degradation. Secondly, for video streaming mode, we consider the HTTP-based video streaming model exploiting multipath with LTE and WiFi networks. Based on analysis of the energy consumption and data usage for the video streaming services, we propose a multi-RAT based video streaming algorithm that balances between the video quality, i.e., the performance metric, and the total playback time with currently given battery energy and data quota. Finally, we cope with the battery energy leakage issue of the smartphone in the standby mode due to intermittent traffic generated by some applications running on background. We analyze the energy-consuming factors in the standby mode and smartphone usage patterns of multiple users, and then, propose a usage pattern-aware deep sleep operation algorithm to save the battery energy in the standby mode. Simulation results based on real measurement data of the smartphone show that the ESPA algorithms indeed choose the best operational mode by maintaining dynamic balance among the performance, energy consumption, and service charge considering the currently provided services and the remaining resources.Abstract i Contents iv List of Tables vii List of Figures viii 1 Introduction 1 1.1 Energy, Service Charge, and Performance aware Multi-RAT Operation Policies for Smartphone 1.2 Overview of Existing Approaches 1.2.1 Multi-attribute based network selection 1.2.2 Energy and quota-aware video streaming services 1.2.3 Multi-path based approaches 1.3 Main Contributions 1.3.1 File transfer mode 1.3.2 Video streaming mode 1.3.3 Standby mode 1.4 Organization of the Dissertation 2 File Transfer Mode 2.1 Introduction 2.2 System Model 2.3 Problem Formulation 2.3.1 T-E-Q cost modeling 2.3.2 Optimization problem 2.4 Numerical Analysis 2.5 Proposed Algorithm 2.5.1 Bi-directional linear search algorithm 2.5.2 Dynamic update algorithm 2.6 Performance Evaluation 2.7 Summary 3 Video Streaming Mode 3.1 Introduction 3.2 System Model 3.2.1 HTTP-based playback model 3.2.2 LTE/WiFi-based multipath video streaming model 3.3 Chunk Download Cycle based Analysis 3.3.1 Data and energy consumption rate 3.3.2 Expected waste of data and energy 3.4 Proposed Scheme 3.4.1 Problem formulation 3.4.2 Subproblem I: Playback time maximization 3.4.3 Subproblem II: Balancing between encoding rate and total playback time 3.5 Performance Evaluation 3.5.1 Maximization of playback time with a single path 3.5.2 Balancing between video quality and playback time with LTE/WiFi multiple networks 3.6 Summary 4 Standby Mode 4.1 Introduction 4.2 Standby Mode Power Anatomy of Smartphones 4.2.1 Low power mode operation 4.2.2 Power consumption for background traffic 4.2.3 WiFi MAC overhead issue 4.3 Usage Log-based Idle Duration Analysis 4.3.1 User-specific daily distribution of idle duration 4.3.2 All-day distribution 4.3.3 Activity/inactivity time separation 4.4 Proposed Algorithm 4.4.1 Learning phase 4.4.2 Deep Sleep Mode (DSM) operation 4.5 Performance Evaluation 4.5.1 Performance comparison 4.5.2 Effect of Tonoff 4.6 Summary 5 Conclusion 5.1 Concluding Remarks Abstract (In Korean)Docto

Elastic phone : towards detecting and mitigating computation and energy inefficiencies in mobile apps

Mobile devices have become ubiquitous and their ever evolving capabilities are bringing them closer to personal computers. Nonetheless, due to their mobility and small size factor constraints, they still present many hardware and software challenges. Their limited battery life time has led to the design of mobile networks that are inherently different from previous networks (e.g., wifi) and more restrictive task scheduling. Additionally, mobile device ecosystems are more susceptible to the heterogeneity of hardware and from conflicting interests of distributors, internet service providers, manufacturers, developers, etc. The high number of stakeholders ultimately responsible for the performance of a device, results in an inconsistent behavior and makes it very challenging to build a solution that improves resource usage in most cases. The focus of this thesis is on the study and development of techniques to detect and mitigate computation and energy inefficiencies in mobile apps. It follows a bottom-up approach, starting from the challenges behind detecting inefficient execution scheduling by looking only at apps’ implementations. It shows that scheduling APIs are largely misused and have a great impact on devices wake up frequency and on the efficiency of existing energy saving techniques (e.g., batching scheduled executions). Then it addresses many challenges of app testing in the dynamic analysis field. More specifically, how to scale mobile app testing with realistic user input and how to analyze closed source apps’ code at runtime, showing that introducing humans in the app testing loop improves the coverage of app’s code and generated network volume. Finally, using the combined knowledge of static and dynamic analysis, it focuses on the challenges of identifying the resource hungry sections of apps and how to improve their execution via offloading. There is a special focus on performing non-intrusive offloading transparent to existing apps and on in-network computation offloading and distribution. It shows that, even without a custom OS or app modifications, in-network offloading is still possible, greatly improving execution times, energy consumption and reducing both end-user experienced latency and request drop rates. It concludes with a real app measurement study, showing that a good portion of the most popular apps’ code can indeed be offloaded and proposes future directions for the app testing and computation offloading fields.Los dispositivos móviles se han tornado omnipresentes y sus capacidades están en constante evolución acercándolos a los computadoras personales. Sin embargo, debido a su movilidad y tamaño reducido, todavía presentan muchos desafíos de hardware y software. Su duración limitada de batería ha llevado al diseño de redes móviles que son inherentemente diferentes de las redes anteriores y una programación de tareas más restrictiva. Además, los ecosistemas de dispositivos móviles son más susceptibles a la heterogeneidad de hardware y los intereses conflictivos de las entidades responsables por el rendimiento final de un dispositivo. El objetivo de esta tesis es el estudio y desarrollo de técnicas para detectar y mitigar las ineficiencias de computación y energéticas en las aplicaciones móviles. Empieza con los desafíos detrás de la detección de planificación de ejecución ineficientes, mirando sólo la implementación de las aplicaciones. Se muestra que las API de planificación son en gran medida mal utilizadas y tienen un gran impacto en la frecuencia con que los dispositivos despiertan y en la eficiencia de las técnicas de ahorro de energía existentes. A continuación, aborda muchos desafíos de las pruebas de aplicaciones en el campo de análisis dinámica. Más específicamente, cómo escalar las pruebas de aplicaciones móviles con una interacción realista y cómo analizar código de aplicaciones de código cerrado durante la ejecución, mostrando que la introducción de humanos en el bucle de prueba de aplicaciones mejora la cobertura del código y el volumen de comunicación de red generado. Por último, combinando la análisis estática y dinámica, se centra en los desafíos de identificar las secciones de aplicaciones con uso intensivo de recursos y cómo mejorar su ejecución a través de la ejecución remota (i.e.,"offload"). Hay un enfoque especial en el "offload" no intrusivo y transparente a las aplicaciones existentes y en el "offload"y distribución de computación dentro de la red. Demuestra que, incluso sin un sistema operativo personalizado o modificaciones en la aplicación, el "offload" en red sigue siendo posible, mejorando los tiempos de ejecución, el consumo de energía y reduciendo la latencia del usuario final y las tasas de caída de solicitudes de "offload". Concluye con un estudio real de las aplicaciones más populares, mostrando que una buena parte de su código puede de hecho ser ejecutado remotamente y propone direcciones futuras para los campos de "offload" de aplicaciones

Elastic phone : towards detecting and mitigating computation and energy inefficiencies in mobile apps

Mobile devices have become ubiquitous and their ever evolving capabilities are bringing them closer to personal computers. Nonetheless, due to their mobility and small size factor constraints, they still present many hardware and software challenges. Their limited battery life time has led to the design of mobile networks that are inherently different from previous networks (e.g., wifi) and more restrictive task scheduling. Additionally, mobile device ecosystems are more susceptible to the heterogeneity of hardware and from conflicting interests of distributors, internet service providers, manufacturers, developers, etc. The high number of stakeholders ultimately responsible for the performance of a device, results in an inconsistent behavior and makes it very challenging to build a solution that improves resource usage in most cases. The focus of this thesis is on the study and development of techniques to detect and mitigate computation and energy inefficiencies in mobile apps. It follows a bottom-up approach, starting from the challenges behind detecting inefficient execution scheduling by looking only at apps’ implementations. It shows that scheduling APIs are largely misused and have a great impact on devices wake up frequency and on the efficiency of existing energy saving techniques (e.g., batching scheduled executions). Then it addresses many challenges of app testing in the dynamic analysis field. More specifically, how to scale mobile app testing with realistic user input and how to analyze closed source apps’ code at runtime, showing that introducing humans in the app testing loop improves the coverage of app’s code and generated network volume. Finally, using the combined knowledge of static and dynamic analysis, it focuses on the challenges of identifying the resource hungry sections of apps and how to improve their execution via offloading. There is a special focus on performing non-intrusive offloading transparent to existing apps and on in-network computation offloading and distribution. It shows that, even without a custom OS or app modifications, in-network offloading is still possible, greatly improving execution times, energy consumption and reducing both end-user experienced latency and request drop rates. It concludes with a real app measurement study, showing that a good portion of the most popular apps’ code can indeed be offloaded and proposes future directions for the app testing and computation offloading fields.Los dispositivos móviles se han tornado omnipresentes y sus capacidades están en constante evolución acercándolos a los computadoras personales. Sin embargo, debido a su movilidad y tamaño reducido, todavía presentan muchos desafíos de hardware y software. Su duración limitada de batería ha llevado al diseño de redes móviles que son inherentemente diferentes de las redes anteriores y una programación de tareas más restrictiva. Además, los ecosistemas de dispositivos móviles son más susceptibles a la heterogeneidad de hardware y los intereses conflictivos de las entidades responsables por el rendimiento final de un dispositivo. El objetivo de esta tesis es el estudio y desarrollo de técnicas para detectar y mitigar las ineficiencias de computación y energéticas en las aplicaciones móviles. Empieza con los desafíos detrás de la detección de planificación de ejecución ineficientes, mirando sólo la implementación de las aplicaciones. Se muestra que las API de planificación son en gran medida mal utilizadas y tienen un gran impacto en la frecuencia con que los dispositivos despiertan y en la eficiencia de las técnicas de ahorro de energía existentes. A continuación, aborda muchos desafíos de las pruebas de aplicaciones en el campo de análisis dinámica. Más específicamente, cómo escalar las pruebas de aplicaciones móviles con una interacción realista y cómo analizar código de aplicaciones de código cerrado durante la ejecución, mostrando que la introducción de humanos en el bucle de prueba de aplicaciones mejora la cobertura del código y el volumen de comunicación de red generado. Por último, combinando la análisis estática y dinámica, se centra en los desafíos de identificar las secciones de aplicaciones con uso intensivo de recursos y cómo mejorar su ejecución a través de la ejecución remota (i.e.,"offload"). Hay un enfoque especial en el "offload" no intrusivo y transparente a las aplicaciones existentes y en el "offload"y distribución de computación dentro de la red. Demuestra que, incluso sin un sistema operativo personalizado o modificaciones en la aplicación, el "offload" en red sigue siendo posible, mejorando los tiempos de ejecución, el consumo de energía y reduciendo la latencia del usuario final y las tasas de caída de solicitudes de "offload". Concluye con un estudio real de las aplicaciones más populares, mostrando que una buena parte de su código puede de hecho ser ejecutado remotamente y propone direcciones futuras para los campos de "offload" de aplicaciones.Postprint (published version

Demystifying Internet of Things Security

Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms

The Effective Transmission and Processing of Mobile Multimedia

Ph.DDOCTOR OF PHILOSOPH

IP Flow Mobility support for Proxy Mobile IPv6 based networks

The ability of offloading selected IP data traffic from 3G to WLAN access networks is considered a key feature in the upcoming 3GPP specifications, being the main goal to alleviate data congestion in celular networks while delivering a positive user experience. Lately, the 3GPP has adopted solutions that enable mobility of IP-based wireless devices relocating mobility functions from the terminal to the network. To this end, the IETF has standardized Proxy Mobile IPv6 (PMIPv6), a protocol capable to hide often complex mobility procedures from the mobile devices. This thesis, in line with the mentioned offload requirement, further extends Proxy Mobile IPv6 to support dynamic IP flow mobility management across access wireless networks according to operator policies. In this work, we assess the feasibility of the proposed solution and provide an experimental analysis based on a prototype network setup, implementing the PMIPv6 protocol and the related enhancements for flow mobility support. *** La capacità di spostare flussi IP da una rete di accesso 3G ad una di tipo WLAN è considerata una caratteristica chiave nelle specifiche future di 3GPP, essendo il principale metodo per alleviare la congestione nelle reti cellulari mantenendo al contempo una ragionevole qualità percepita dall'utente. Recentemente, 3GPP ha adottato soluzioni di mobilità per dispositivi con accesso radio basato su IP, traslando le funzioni di supporto dal terminale alla rete, e, a questo scopo, IETF ha standardizzato Proxy Mobile IPv6 (PMIPv6), un protocollo studiato per nascondere le procedure di mobilità ai sistemi mobili. Questa tesi, in linea con la citata esigenza di spostare flussi IP, estende ulteriormente PMIPv6 per consentire il supporto alla mobilità di flussi tra diverse reti di accesso wireless, assecondando le regole e/o politiche definite da un operatore. In questo lavoro, ci proponiamo di asserire la fattibilità della soluzione proposta, fornendo un'analisi sperimentale di essa sulla base di un prototipo di rete che implementa il protocollo PMIPv6 e le relative migliorie per il supporto alla mobilità di flussiope

Telecommunication Systems

This book is based on both industrial and academic research efforts in which a number of recent advancements and rare insights into telecommunication systems are well presented. The volume is organized into four parts: "Telecommunication Protocol, Optimization, and Security Frameworks", "Next-Generation Optical Access Technologies", "Convergence of Wireless-Optical Networks" and "Advanced Relay and Antenna Systems for Smart Networks." Chapters within these parts are self-contained and cross-referenced to facilitate further study

Accelerating Network Functions using Reconfigurable Hardware. Design and Validation of High Throughput and Low Latency Network Functions at the Access Edge

Providing Internet access to billions of people worldwide is one of the main technical challenges in the current decade. The Internet access edge connects each residential and mobile subscriber to this network and ensures a certain Quality of Service (QoS). However, the implementation of access edge functionality challenges Internet service providers: First, a good QoS must be provided to the subscribers, for example, high throughput and low latency. Second, the quick rollout of new technologies and functionality demands flexible configuration and programming possibilities of the network components; for example, the support of novel, use-case-specific network protocols. The functionality scope of an Internet access edge requires the use of programming concepts, such as Network Functions Virtualization (NFV). The drawback of NFV-based network functions is a significantly lowered resource efficiency due to the execution as software, commonly resulting in a lowered QoS compared to rigid hardware solutions. The usage of programmable hardware accelerators, named NFV offloading, helps to improve the QoS and flexibility of network function implementations. In this thesis, we design network functions on programmable hardware to improve the QoS and flexibility. First, we introduce the host bypassing concept for improved integration of hardware accelerators in computer systems, for example, in 5G radio access networks. This novel concept bypasses the system’s main memory and enables direct connectivity between the accelerator and network interface card. Our evaluations show an improved throughput and significantly lowered latency jitter for the presented approach. Second, we analyze different programmable hardware technologies for hardware-accelerated Internet subscriber handling, including three P4-programmable platforms and FPGAs. Our results demonstrate that all approaches have excellent performance and are suitable for Internet access creation. We present a fully-fledged User Plane Function (UPF) designed upon these concepts and test it in an end-to-end 5G standalone network as part of this contribution. Third, we analyze and demonstrate the usability of Active Queue Management (AQM) algorithms on programmable hardware as an expansion to the access edge. We show the feasibility of the CoDel AQM algorithm and discuss the challenges and constraints to be considered when limited hardware is used. The results show significant improvements in the QoS when the AQM algorithm is deployed on hardware. Last, we focus on network function benchmarking, which is crucial for understanding the behavior of implementations and their optimization, e.g., Internet access creation. For this, we introduce the load generation and measurement framework P4STA, benefiting from flexible software-based load generation and hardware-assisted measuring. Utilizing programmable network switches, we achieve a nanosecond time accuracy while generating test loads up to the available Ethernet link speed